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---
license: mit
base_model: cointegrated/rut5-base-multitask
tags:
- generated_from_trainer
model-index:
- name: finetune_t5_base_only_hack
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# finetune_t5_base_only_hack
This model is a fine-tuned version of [cointegrated/rut5-base-multitask](https://huggingface.co/cointegrated/rut5-base-multitask) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4584
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0004
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 8
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.8215 | 3.86 | 150 | 1.5392 |
| 1.579 | 7.72 | 300 | 1.4584 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
|